Background: Persistent high-risk human papillomavirus (HPV) infection is a necessary prerequisite for development of cervical cancer and its precursor lesion, high-grade squamous intraepithelial lesion (HSIL). However, HPV infection is not sufficient to drive this process, and genetic and environmental factors may also play a role. Methods/Design: The Cervical Cancer, Genetics and Environment Twin Study was established to investigate the environmental and genetic influences on variation in susceptibility to cervical pre-cancer in 25- to 69-year-old monozygotic (MZ) and dizygotic (DZ) twins recruited through the Australian Twin Registry. Reviews of Papanicolaou (Pap) screening histories were undertaken to identify individual women with a history of an abnormal Pap test. This was followed by detection of HPV in archival Pap smears of selected twin pairs to determine HPV persistence. Selected twin pairs also completed a detailed questionnaire on socio-demographic characteristics, sexual behavior, and HPV knowledge. In future analyses, under the assumptions of the classical twin design, case-wise concordance for persistent HPV infection and HSIL will be calculated for MZ and DZ twin pairs, and twin pairs (both MZ and DZ) who are discordant for the above outcomes will be used to assess the contributions of measured environmental risk factors. Discussion: The study examines factors related to HPV persistence and development of HSIL among female MZ and DZ twins. The results will contribute to our understanding of the natural history of cervical HPV infection and the relative contributions of genetic and environmental factors in disease progression.

The objective was to examine the association between several obesity-related nongenetic behaviors and body mass index (BMI) and waist circumference (WC) in young adult twins using reports from both twins on their similarities and differences. A total of 713 monozygotic (MZ) and 698 same-sex dizygotic (DZ) twin pairs aged 22–28 years filled in structured questionnaires to compare their eating, physical activity and dieting behavior with their co-twin's behavior, and to report their own eating and exercise habits. In both MZ and DZ pairs, the co-twins for whom both twin pair members concordantly answered that this twin eats more, snacks more, eats more fatty foods and sweet and fatty delicacies, chooses less healthy foods, eats faster and exercises less, had significantly higher BMIs (0.6–2.9 kg/m2) and WCs (1.5–7.5 cm). Multivariate regression analysis identified co-twin differences in the amount of food consumed as the strongest independent predictor of intrapair differences in BMI (β = 0.63 and 1.21, for MZ and DZ, respectively, p < .001) and WC (β = 1.52 and 3.53, for MZ and DZ, respectively, p < .001). Higher leisure-time physical activity and healthier dietary choices clustered in the same subjects. The measurement of habitual dietary intake and physical activity has previously relied on subjective self-reports that are prone to misreporting. By using comparative measures within twin pairs we found that the amount of food consumed is the major contributor to obesity independent of genetic predisposition.

The current article examines the assumptions of the MZ co-twin control method that has been applied in attempts to gain more accurate estimates of the returns to education by naturally ‘controlling’ for individual differences on which MZ twins are matched. The current study examined 1738 MZ and 926 DZ twins from Minnesota, including 133 pairs of MZ and 101 pairs of DZ twins discordant for university attendance. They were assessed prospectively on personality, intelligence, GPA, and academic motivation; a subset also has reported income at age 29. MZ twins discordant for university attendance differed significantly and prospectively on verbal IQ, personality traits, and GPA. While MZ co-twin control studies can provide more accurate estimates of the returns to education than analyses of single individuals, these studies do not entirely obviate the need to control for differences between university students and non-students that predate university attendance and might account for income differentials and even non-monetary outcomes.